jurafsky&martin_3rdEd_17 (1).pdf

Hyperarticulation increases in f0 range pause

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hyperarticulation, increases in F0 range, pause duration, and word duration, generally normalized by the values for previous sentences ASR features ASR confidence, language model probability 29.3 Dialogue Policy The goal of the dialog policy is to decide what action the system should take next, dialog policy that is, what dialog act to generate. We begin in the next section by introducing one specific dialog policy decision, relating to confirmation: how we confirm to the user what we think she said. We then sketch a basic policy algorithm that could apply to all decisions. Finally, once a speech act has been generated, the natural language generation component needs to generate the text of a response to the user. 29.3.1 Generating Dialogue Acts: Confirmation and Rejection Modern dialog systems often make mistakes. It is therefore important for dialog systems to make sure that they have achieved the correct interpretation of the user’s input. This is generally done by two methods: confirming understandings with the user and rejecting utterances that the system is likely to have misunderstood. Various strategies can be employed for confirmation with the user. When using the explicit confirmation strategy, a system asks the user a direct question to con- explicit confirmation firm the system’s understanding, like the two examples below in which the system asks a (boldface) yes-no confirmation questions: S: Which city do you want to leave from? U: Baltimore. S: Do you want to leave from Baltimore? U: Yes. U: I’d like to fly from Denver Colorado to New York City on September twenty first in the morning on United Airlines S: Let’s see then. I have you going from Denver Colorado to New York on September twenty first. Is that correct? U: Yes
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450 C HAPTER 29 A DVANCED D IALOG S YSTEMS When using the implicit confirmation strategy, a system instead uses the demon- implicit confirmation stration or display grounding strategies described above, repeating back the system’s understanding as part of asking the next question, as in the two examples below: U: I want to travel to Berlin S: When do you want to travel to Berlin? U2: Hi I’d like to fly to Seattle Tuesday Morning A3: Traveling to Seattle on Tuesday, August eleventh in the morning. Your full name? Explicit and implicit confirmation have complementary strengths. Explicit con- firmation makes it easier for users to correct the system’s misrecognitions since a user can just answer “no” to the confirmation question. But explicit confirmation is awkward and increases the length of the conversation ( Danieli and Gerbino 1995 , Walker et al. 1998 ). The explicit confirmation dialog fragments above sound non- natural and definitely non-human; implicit confirmation is much more conversation- ally natural.
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